The nested modelling approach of WP3 relies at the larger scale on RCMs simulations, which in ST 2.1.1 will provide basic information on expected climatic changes in the Alpine area at different regional spatial scales. Simulations will performed using two different regional climate models, namely “REMO” (Jacob, 2001) and the ICTP-RegCM3. Both models will cover the same simulation period and will simulate the same selection of the IPCC scenarios. At MPI several transient climate change simulations until 2100 at horizontal resolutions of 25 and 50 km with a model domain covering the entire European area (carried out within the European ENSEMBLES project) will be available the start of the project. These experiments will provide boundary conditions for dedicated REMO simulations for the Alpine area at a very high resolution of 10 x 10 km². For the central and northern part of the Alps such experiments are already available for the period 1950-2100 and for the SRES emission scenarios B1, A1B and A2. The new experiments will focus on the time horizon 1960-2050 and will include a novel and recently developed dynamic glacier scheme (Kotlarski, 2007), a unique feature of the RCM REMO. This scheme accounts for mountain glaciers on a subgrid and allows for an independent estimate of the future evolution of Alpine glaciers in addition to the forcing of dedicated mass balance models for individual glaciers or mesoscale river catchments by RCM data (ST 2.3.1 and T 2.2). In order to assess possible feedbacks of changing vegetation characteristics as a result of climatic changes, an additional REMO simulation will be carried out including a bi-directional coupling to the LPJ-GUESS biosphere model (see T 2.5). Investigation of
feedback mechanisms related to changes in vegetation characteristics and their influence on the simulated climate change signal will be thus made possible.

The recently-upgraded ICTP-RegCM3 model will be used in parallel to REMO to generate multi-decadal simulations over the investigated domains with a horizontal grid size of 10-15 km. The initial simulation will focus on the Rhone and Po valley and will cover the period 1960-2050. Further simulations will include the other European regions and non-European mountain areas targeted by the project. Boundary conditions for the European simulations will be obtained from corresponding intermediate resolution experiments (Dx = 25-50 km) completed as part of other European projects, such as ENSEMBLES. A novel aspect of these simulations is that the RegCM will employ its capability of carrying out land surface calculations on a finer grid taking into account fine scale topography and land surface information. For ACQWA it is planned to carry out simulations using 1 km sub-grid surface calculations. These calculations will enable to bridge the scales between climate model information and input for hydrology calculations. At 1 km resolution Alpine lakes can be resolved, and a one dimensional lake model coupled to the RegCM3 system will be used to carry out the lake calculations.

In order to satisfy the demand of the basin scale integrated hydrological models and of the local/point scale models (T 3.2 and 3.3), as well as some assessment carried out in WP3, the RCMs output require downscaling to the space-time scales suitable to drive these models. Depending on the basin size, the spatial scale can vary from the upper limit of 1´1 km to a few tens of meters, whereas the characteristic temporal scales are often sub-daily and hourly. Throughout the ACQWA project various methods are applied to further refine the results of the regional climate models operating on a 10 km grid to a 1 km grid or to the "point scale" (statistical methods), respectively: Further dynamical downscaling and a subgrid-scale land-surface model (ST 3.1.1), and statistical methods in T 3.4 for deriving local scale precipitation. In this Task both dynamic and statistical/stochastic downscaling methods will be collected and supplemented as described below to achieve the space-time resolution required by the models used in T 3.2.

The 10´10 km REMO experiments will be accordingly downscaled to force by means of a novel double nesting procedure. This will be achieved by using the REMO simulations to drive in a nested mode the non-hydrostatic RCM MM5 (Dudhia, 1993) with a target resolution of 3x3 km and 1x1 km. In this way, a physically consistent simulation of local scale climatic features, e.g., as triggering factors for local hydrological extremes and other hazards is possible and can be both linked to hydrological and process models of T 2.2 and 2.3, and used to perform direct analysis of extremes as described in T 2.4. The spatial resolution achieved by the double nesting scheme will allow also to test and improve the efficiency of statistical downscaling techniques that will be also used to define scenarios at the smallest scales required by the analysis.

While the dynamic downscaling will provide a spatial resolution of 1´1 km for shorter time periods, statistical and stochastic downscaling techniques will be applied to generate scenarios at the “point scale” (simulated station data) and with the purpose of producing multiple scenarios according to Monte Carlo methods. The spatial resolution achieved by dynamical downscaling will allow to cross-validate and to improve the efficiency of statistical techniques and will be also used to enhance spatial interpolation of point scale datasets.

A special focus of ST 3.1.2 will be on evaluating the uncertainty associated with these fine-scale downscaling methods by analysing the ensemble of methods using probabilistic techniques (e.g., Déqué et al., 2007). The uncertainty component due to the driving RCM simulations at resolutions 10-25 km and originating from the choice of a specific model or a specific model setup will be additionally assessed via a comparison of all available RCM experiments of the respective scale.

Furthermore, ST 3.1.2 will exploit the multiple simulations of surface variables related to the hydrological cycle in climate models (T 3.1), hydrological models (T 3.2) and the biosphere model (ST 3.3.5 and 4.2.5) for cross-validation and uncertainty estimation of those variables.

Task 3.2 is built around the implementation of three distributed hydrological models that will use the downscaled scenarios developed in ST 3.1.2 to simulate the response to CC scenarios at the catchment scale. The selected models are the TOPKAPI model (Todini and Ciarapica, 2001; Zhiyu and Todini, 2002; Liu et al, 2005), the FEST model (Mancini, 1990; Montaldo et al., 2004; Montaldo et al., 2007) and the CHyM. All of the models have the following characteristics: raster based (resolution dictated by DEM availability and catchment scale, approx. range 50 to 500 m grid size); physically based/oriented; continuous in time with hourly resolution; explicit in the soil/and component; internally consistent. They can account and produce distributed output scenarios for the following processes: snow and ice accumulation/melting, interception, evaporation/evapotranspiration, infiltration/soil moisture, streamflow, groundwater storage. Moreover, they can be easily coupled and/or interfaced with modules simulating the occurrence of shallow landslides/soil slips, surface erosion and sediment transport.

The three models will be used for general simulations of all the case studies, thus providing the possibility to run an intercomparison among the different approaches. Inputs to the models will be provided by the downscaled scenarios produced in ST 3.1.2. In addition, investigation of specific basin response issues will be addressed by single model applications on the basis of specific model specialization in simulating a given process. This will allow focusing on basin wide analysis of specific impact analyses, such as that of erosion and its interplay with evolving vegetation cover. The various model outputs will be available in form continuous hourly time series of streamflow, soil moisture, evaporation/evapotranspiration, etc., including extremes, which will be directly used or properly aggregated to provide the appropriate input for the impact analysis carried out in WP4. These outputs will additonally provide the basis to investigate by means of simplified approaches the impact of altered streamflow regimes on the recharge of river-fed groundwater systems.

A novel approach to account for the sub-grid variability at the basin scale will be implemented. This is particularly important for modelling of basin scales that require the use of a model raster size that cannot resolve properly in space the modifications induced by climatic change. This is for instance the case of glacier processes, of biosphere dynamics and hill slope stability. The hydrological models will be thus complemented by detailed and process oriented local models that will be developed in ST 3.3.1 to 3.3.4. Scaling-up techniques will be developed to nest the detailed models (or the results of their simulations) into the distributed model catchment scale, for instance by borrowing techniques already used for the nesting of climate models. Detailed models will be also used to simulate local specific scenarios.

Task 3.3: Sub-grid variability of the response (local/point scale)

This Task will develop models of the sub-grid variability of the response that will either be nested into the basin scale models or will provide to them an external input which is the result of refined modelling at space-time scales which are more appropriate to investigate the effect of climatic change on a given process. The sub-grid models will address the most sensitive compartments of the complex interaction between water, vegetation and landscape. Accordingly, local models will be developed to address the response of glaciers to climatic change induced enhanced melt forcing, the intra-annual and interannual modification of the snowpack evolution, the response of soil moisture dynamics, and the response of the vegetation systems. All of these compartments are directly influenced by climatic change and its effects on he hydrological cycle, and, in turn, affect water resources by means of feedback mechanisms. Other small scale investigations of processes that are less indirectly connected to changes in water resources are deliberately left out to favour a targeted work.

The detailed understanding of how the snowpack seasonal evolution will be affected by CC is a key element to understand how different the accumulation and melting processes will occur over glaciers and, more in general, in mountainous areas. Modifications in the snowpack, such as accelerated aging, will eventually intensify the seasonal accumulation-ablation cycle thus enhancing the shift in water resources availability from winter snow storages, which are already endangered by a shift of snowfall towards liquid precipitation. The role of ST 3.3.1 is therefore to investigate what is the effect of CC on the modifications of the snowpack throughout the winter season by means of the physically based numerical model CROCUS (Brun et al., 1989 and 1992). This is a numerical snow model that calculates the evolution of the energy and mass balance of the snow cover. It uses only meteorological conditions and simulates the evolution of temperature, density, liquid water content and layering of the snow pack. The physical basis of the model allows to simulate snow metamorphism in near surface and deeper layers and to represent each snow type separately, thus providing snow albedo and extinction coefficients estimates that are derived throughout the season on the basis of the surface snow type, size and age.

The validation of the model will be based on simulations fed by the past and current climate baselines (T 2.2) and assessed by means of the remotely sensed data (T 2.3). The assessment of the snowpack evolution under CC fording will be carried out at the local/point scale using the downscaled RCMs scenarios (ST 3.1.2). The outputs will be both analysed at the local scale and used to drive accumulation and melt models used by detailed glacier mass balance models in ST 3.3.2 and by basin scale distributed models in T 3.2. Among others, this ST will provide to models used in ST 3.3.2 and T 2.2. CC dependent parameterizations of, e.g., snow density, albedo and roughness. This will allow to achieve more realistic glacier and basin scale snow- and ice-melt simulations with parsimonious models, that account for a dynamic parameterization, which captures process interactions and feedbacks with climate forcing.

A by-product of this modelling construct, which will be eventually addressed in the project is the improvement of the land surface schemes used presently by RCMs to account for the snow components.

The overall aim of this ST is to predict the changing magnitude and timing of water production from glacierized basins characterized by different morphological and ice features under CC at high resolution scales. This will be based on detailed studies at selected and characteristic glaciers, thereby including debris covered glaciers. The analysis carried out in this ST will provide, on the one hand, a detailed investigation of several exemplary glacier case studies, that will help to depict the likely impact of CC at the glacier scale (mass balance and retreat, water production) as a function of the glacier characteristics; on the other hand, the ST will provide a way to integrate the sub-grid variability into the glacier model components of the basin scale hydrological models (T 2.2), by means of techniques to scale up the local models and/or model results, which will be tested within the project.

Glacier candidates for this ST are: Haut Glacier d’Arolla, in the southern Swiss Alps, which is small alpine valley glacier that has been the object of extensive glaciological investigations in the past decades, including by the investigators (Strasser et al., 2004; Pellicciotti et al., 2005), thus offering an ideal case study for the abundance of meteorological and geophysical data collected; Gorner glacier, also in the southern Alps of Switzerland and close to Haut Glacier d’Arolla, which however experiences a distinct precipitation regime that affects the accumulation and summer melt process. The glacier is also a much bigger and complex glaciated system ranging a broad span of elevations and it is not entirely temperate, thus providing an optimal site to test models developed for smaller temperate glaciers (Kretzt et al, 2007); Aletsch glacier, in the Swiss Alps, where one of the longest time series of mass balance and runoff measurements exists, which can be therefore used as an ideal case study to test the model developed by the investigators to simulate the mass balance evolution (Huss et al., 2007); Tsa de la Tsa glacier, in the Italian Alps, where the investigators have been carrying out a pilot study to understand the effect of climatic changes on the melt regime and the water production from the glacier (Cremonese et al. 2007), which allowed us to test models transferability and their robustness in conditions of scarcity of some of the input data; Miage glacier, on the southern side of the Mont Blanc Massif, which is among the largest debris covered glaciers in the Alps and an excellent site for investigating the feedbacks between glacier retreat, expansion of debris covers and melt reduction due to debris cover. The investigators have established a meteorology and energy balance program at this site and are developing existing models of glacier melt to make them applicable to debris covered ice (Brock et al., in press); and Juncal Norte glacier, in the dry Andes of Chile, situated in a very different climatic settings, where precipitations are scarce and sublimation plays a crucial role in the glacier surface energy balance, and where the investigators have been conducting an extensive field campaign and interdisciplinary glaciological and hydrological project for the past two years (see for details Work package 5.3).

Existing glacier mass and energy balance models (Pellicciotti, 2004; Pellicciotti et al, 2005; Huss et al., 2007, Brock et al. 2000) will be used and adapted to the project according to the quality and resolution of input data. As the influence of CC on melt is directly connected to glacier retreat, the latter will be specifically investigated by coupling the mass balance with evolution models of the glacier morphology (both advanced, where data about the 3D structure of the glacier are available, and based on simple flow models, where no morphological data are available) to account for more realistic retreat response, and ultimately for more realistic response of melt to CC. This will require, among others, improvements to existing models that concern:

- the ablation modelling, that can be greatly improved in both accuracy and temporal/spatial resolution by incorporating parameterisations for incoming shortwave radiation and albedo, which do not require additional data, thus enhancing the model transferability for CC impact studies and for integration into the basin scale hydrological models; - a dynamic parameterisation to account for snowpack morphological changes as induced by CC scenarios and simulated in ST 2.3.1, thus enabling to account, e.g., for variable snow density and surface roughness, as modified by the effect of CC throughout the scenario horizon; - the incorporation of feedbacks between glacier response to climate change and mass balance in order to give realistic forecasts of future water production as glaciers shrink, thus considering

positive feedbacks, in the case of increased advection of heat and longwave radiation from bare rock slopes and decreased albedo during hot and drought conditions (e.g. summer 2003);

negative feedbacks, in the case of increased debris cover insulation and retreat of glaciers to higher/colder locations;

- the modelling of melt water outflow from glacier models, which will be routed using linear and/or nonlinear reservoirs models, which will be dynamically parameterized throughout the season, at a range of timescales and spatial resolutions dictated by the requirements of the detailed glacier modelling and of the need for integration into basin scale hydrological models (WP2.2).

The above models will be tested, before their use in scenario simulation, using the past and current baseline scenarios developed in T1.2 and, in addition, on recently analysed mass-balance time-series in seasonal resolution since 1865 that have been modelled for Alpine glaciers, based on in-situ observations of accumulation and melt, ice-volume changes determined by differential analysis of digital elevation models, and meteorological data (Huss et al., 2007).

Subtask 3.3.3: Impact of climate warming on the stability of hanging glaciers in the alps

The analysis of ST 3.3.2 will highlight how the CC induced diffused glacier retreat will produce new areas at risk for icefalls or ice avalanches from hanging glaciers. Although relatively rare, these can pose severe threat to human settlement and infrastructures, thus impacting economic sectors such as hydropower and tourism, which often have their infrastructure in the vicinity of glaciers. Climate warming can affect the stability of hanging glaciers because the thermal conditions, especially at the glacier base, will be modified. Dangerous situations may arise on hanging glaciers if previous cold conditions at the glacier bed become temperate. In such a situation the stability of the whole glacier may be affected, because of sudden ongoing sliding conditions at the glacier base. As shown in recent studies, englacial temperatures at high altitude provide clear evidence of warming over the last two decades. Consequently, it is very important to survey and to model the englacial temperatures for hanging glaciers and to recognize under which conditions instability may occur, in order to enforce appropriate mitigation measures that minimize the impact of such a threat (ST 4.1.1 and 4.2.4).

This ST will therefore contribute to assess the stability conditions of hanging glaciers in the Rhone basin area, by combining the outcomes of the modelling done in ST 3.3.2 with the extrapolation of englacial temperatures based on local temperature scenarios. The rise of englacial temperatures over the last decades will be especially analyzed jointly with the baseline scenarios developed in T 2.2 to assess the plausibility of the numerical modelling for the evolution of the temperature field in these glaciers, before its application for the next decades. In this respect, links between the atmospheric variables of nearby stations at the selected glaciers (e.g. Taconnaz and Weisshorn in the Rhone basin and Grandes Jorasses in the Pô Basin) and the englacial temperatures will be investigated in order to develop a modelling strategy that can predict the evolution of hanging glaciers. The atmospheric warming can indeed have a major impact on the stability of hanging glaciers if their base becomes temperate (0°C). Depending on exposition and on ice advection, the cold ice is generally located above 3’500 m above sea level. At these altitudes, glaciers are frozen to their bed and no sliding occurs. As soon as they become temperate, major parts may be destabilized and large ice avalanches can be formed.

Most of the avaliable studies on the effects of CC predict significant changes of soil moisture. However, very little has been investigated with respect to the variability of such dynamics at the small scale. Because very often in mountainous regions the management scale is small and the heterogeneity of the landscape, vegetation cover and agricultural activities is high, the project will address the small scale variability of the land-atmosphere interactions for a number of different environments, which are typically found in mountain areas. These play a crucial role in controlling, in a direct or indirect way, the hydrological physical processes and the consequent impact on the water resource (Lelieveld et al., 2002) and need to be investigated at small spatial scales (sub-grid/sub-pixel of basin distributed models grid, T 2.2) in order to understand what is the level of complexity of the mathematical representation that has to retained at the grid scale of distributed hydrological models (and at coarser scales, such as in RCMs) as function of the heterogeneity of the cover and its associated response.

These investigations will be carried out by means of Land Surface Models (LSMs) which resolve the mass and energy fluxes at high (spatial and temporal) resolution by solving mass and energy balance equations (e. g., Famiglietti and Wood, 1994; Wigmosta et al., 1994; Albertson and Kiely, 2001; Montaldo and Albertson, 2001). This Subtask will explore the effect of spatial variability of vegetation cover, topography, soil properties on the main mass fluxes at small scales with the purpose of identifying the principal and secondary frequencies of the dynamics of mass fluxes in relation to scale variation and system status. Due to the crucial role played by the vegetation cover on the definition of energy and mass fluxes, this Subtask will develop investigations jointly with ST 2.3.5 (Biosphere modelling), in order to account for appropriate description and/or parameterisation of the vegetation types in the LSM model and (Detto et al . 2006). Output of this analysis will be then used to identify the most appropriate modelling scheme for upscaling to the grid size of the distributed hydrological basin scale models (T 2.2), and for robust simulations at the local scale under CC forcing (Montaldo et al , 2005). Validation of the modelling scheme(s) prior to the application will be done using both ground data and high resolution satellite images, which will be processed in collaboration with T 1.3.

Subtask 3.3.5 Biosphere Model

Forest Ecology, ETH Zurich, Switzerland [A. Wolf, H. Bugmann]

An essential role in the hydrological cycle is played by the vegetation cover. The biosphere is highly important for regional climate and regional hydrology, but feedbacks mechanisms between the hydrological cycle and the biosphere have been generally simplified strongly in previous studies. The project recognises such role and aims at improving the description of the water-vegetation interactions by addressing it in this ST through an appropriate modelling framework (LPJ-GUESS, Smith et al., 2001). This makes use of physiologically based representations of plant-level carbon and water fluxes, to estimate the allocation of assimilated carbon within the plant, and long-term dynamic changes in species distributions. Particularly important is to estimate the variability and the uncertainty of the changes at different space and time scales. To this purpose, the LPJ-GUESS model will be used jointly or coupled with three different types of models running at three different space-time scales, namely RCMs (ST 3.1.1), basin scale hydrological models (T 3.2) and subgrid LSM models (ST 3.3.4). Specifically, the plan is to formulate different parameterisations of LPJ-GUESS to match the levels of detail which are consistent with the partner models. This will enable to account for the highest scale-dependent detail of the biosphere dynamic response to CC, thus highlighting the differences among the various time and space scales, ideally from the individual plant or plant community to the regional scale. The ST will assess the resulting differences in ecosystem carbon and water fluxes, focusing on intra-annual variations, and providing surface variables for runs at different resolutions.

A special attention will be paid at feedback mechanisms. This will be done by assessing the importance of long-term changes in vegetation cover and distribution for the climate predictions by means of a bi-directional coupling with the RCM REMO (ST 3.1.1). In the coupled system a number of the climate model’s land surface parameters will be updated regularly to track the vegetation changes simulated by LPJ-GUESS. In a simpler approach, one RCM climate change scenario will be re-run for comparison purposes, assuming modified land surface characteristics as projected by LPJ-GUESS. In both cases the investigation of feedback mechanisms involved in biosphere-atmosphere exchange processes and their influence on climate change projections is possible.

A similar approach will be used to couple the biosphere model with the hydrological models (T 3.2) and the LSM (ST 3.3.4). The coupling will be scale-dependent and will address primarily the feedback between the soil moisture dynamics and the vegetation responses at the scale used by the basin hydrological model and how this is influenced by the more detailed representation of vegetation transpiration processes in the biosphere model. Additionally, we will investigate how the forest cover and expected changes in forest cover, including afforestation and deforestation (all analyzed in ST 4.2.4) will influence the basin hydrology, e.g. the soil moisture dynamics (T 3.2, ST 3.3.4).

Task 3.4: Extremes and hazards

The Summary for Policy Makers of the IPCC 4th Assessment Report (IPCC, 2007) indicates as likely to very likely the increase of the frequency of the extremes based on GCMs simulations. Because extremes are very often occurring at the basin or local scales and trigger hazards that are localized in space, the ACQWA project plans a dedicated Task to the analysis of the extremes as simulated under the CC forcing by the RCMs and the basin hydrological models, thereby including the detailed analysis of some of the relevant impacting hazards. The outputs of tasks 3.1 (climate scenarios) and 3.2 (catchment response) consist of time series of hydrological variables that will be comprehensively analysed in the frequency domain. Changes in the occurrence of events and in their intensity will be quantified both representing them in the form of traditional analysis based on return period concepts, and investigating them within the context of non-stationary analysis. Modifications of the internal structure of storm rainfall events will be also addressed thus quantifying not only the changes in the mean process, but also identifying the changes to intensity and temporal occurrences that lead to higher variability. More specifically, ST 3.4.1 will implement a frequency analysis of the hydrological extremes and their associated uncertainty, comparing the differences between the recent past and the near future. ST 3.4.2 will address the role of specific atmospheric circulation as main driving mechanisms of extreme precipitation events. Finally, ST 3.4.3 will investigate the consequences of an increased frequency of extreme events on triggering geomorphologic hazards, such as erosion, soil slips and debris flows. All these events can have an impact on sediment loading in rivers that in turn can lead to damage to infrastructure (bridges, dams, riverside communication routes, etc.) located in the watershed.

ST 3.4.1 will focus on a frequency analysis of the hydrological extremes observed in the recent past as compared with those simulated by models at different space and time resolutions when forced with CC scenarios (T 3.1, ST 3.1.2, T 3.2). The most significant hydrological variables, such as temperature, storm rainfall intensities, peak flows, dry spells, and other relevant variables, such as erosion rates, sediment yields, will be investigated (i) to estimate the CC induced modifications of their distributional properties and of the related event intensities and/or magnitudes; (ii) to assess the associated uncertainties by analysing both the historical observations and the generated values; and (iii) to quantify the dependence between their space scales and variability and the intensities of the events. These investigations will be carried out on both the RCM and the basin hydrological model simulations, also addressing the effect of the different downscaling techniques on the spatial variability of the occurrences of extremes. The analysis will be carried out at different temporal scales, using both daily, sub-daily and event variables. Given the non stationary nature of the simulated extremes, appropriate statistical techniques will be selected. Attention will be finally paid at estimating the dependence of the extreme events and their spatial extent and intensity on specific large and mesoscale circulation patterns and on their severity.

Subtask 3.4.2: Mediterranean cyclones and their contribution to mountain hydrology

Universität für Bodenkunde, Vienna, Austria [H. Formayer]

Mediterranean cyclones are one of the most important sources for heavy precipitation events in many parts of the Alps. The flood events in May 1999 and August 2005 in parts of Switzerland, Germany and Austria have been caused by a cutoff lows at the 500 hPa pressure level centred over the Alps and northern Italy, transporting Mediterranean air masses counterclockwise around the Alps to the north side. The role of this cyclonic circulation in a changed climate has not yet been extensively investigated. Subtask 2.4.2 aims at assessing whether RCMs simulations (T 2.1) are capable of reproducing the extreme events of cyclones of Mediterranean origin. This will be done forcing RCM runs with ERA40 dataset (T 1.2) and comparing with historical observations at daily time scale (T 1.2). The analysis will concentrate on specific assessment of the extreme events regime, such as comparing the frequency of occurrence, their intensity, the temporal and spatial shifts, the duration and trajectories. Tools will be specifically designed for an objective analysis. Once the RCMs performance assessment is carried out, ST 2.4.2 will analyse precipitation scenarios as simulated by RCMs with specific reference to the heavy precipitation events originating from Mediterranean cyclones and with focus on the estimation of the prediction bias.

One of the major CC impacts claimed in several studies (e.g. Jomelli et al., 2004, 2007; Goudie, 2006; Stoffel et al., 2007) concerns the increase of water driven hazards of geomorphological nature, such as shallow landslides and soil slips, debris- and mudflows, rockfalls, among others (Milly et al., 2002; Stoffel & Beniston, 2006; Stoffel et al., 2005a, b; Perret et al., 2006). This is essentially due to the expected increase in precipitation extremes (in this project analysed in ST 2.4.1), which in turn may enhance erosion and soil degradation, and to the expected temperature increases that in cryosphere environments will lead to an acceleration of glacier retreat and permafrost degradation. Already in the recent years there is evidence of these types of natural hazards claiming hundreds of lives and millions of Euros in lost property in the European Alps and of impacts of intense precipitation event often reaching far beyond the Alps themselves and affecting by severe flooding of populated lowlands (Beniston, 2006). The results of this investigation will be of importance to evaluate the impact on economical activities of mountain societies (tackled in WP4), as population growth and increasing demand for summer and winter tourism activities will not only enhance the pressure on land use, but also augment the vulnerability of residents or tourists and infrastructure in sensitive environments (Bloetzer et al., 1998).

ST 2.4.3 will accordingly address the assessment of how the current mechanisms and triggers of geomorphological hazards may evolve in a future and changed climate. Specifically, this ST will investigate changes in the number and the severity of these events, in their seasonality, and in their spatial variability. The latter aspect is particularly important in view of the impact analysis, as the potential expansion of the areas at risk will require the implementation of new protection and mitigation strategies (such as the traditional hazard maps and the zonation policies) that account for non-stationarity in minimizing the economic and societal impacts of events over the next decades.

The analysis will be carried out following Stoffel & Beniston (2006) and Stoffel et al. (2007) on the basis of the RCMs predictions at regional scales available from ST 2.1.1 with special focus especially the spatial distribution of the changes and the overall changes of regional proneness. More detailed analysis will be carried out on the basis of simulations caried out by distributed hydrological models. These will provide, on the one hand, the boundary conditions (e.g. sediment supply and catchment wetness) to analyse at pilot sites the changes in frequency and intensities of debris flows; on the other hand, they will be coupled to dedicated soil slip models (e.g. Iverson, 2000) to investigate at a smaller scale the changes of the frequency and temporal evolution of soil slips, the latter aspect being particularly important to understand the role of warning systems in a future climate.